MATHEMATICAL MODEL FOR CALCULATING THE EXPERT'S COMPETENCY LEVEL

This article describes empirical research results regarding the "history effect" in software quality evaluation processes. Most software quality models and evaluation processes models assume that software quality may be deterministically evaluated, especially when it is evaluated by experts. Consequently, software developers focus on the technical characteristics of the software product. A similar assumption is common in most engineering disciplines. However, in regard to other kinds of goods, direct violations of the assumption about objective evaluation were shown to be affected by the consequences of cognitive processes limitations. Ongoing discussion in the area of behavioral economics raises the question: are the experts prone to observation biases? If they are, then software quality models overlook an important aspect of software quality evaluation. This article proposes an experiment that aims to trace the influence of users' knowledge on software quality assessment. Measuring the influence of single variables for the software quality perception process is a complex task. There is no valid quality model for the precise measurement of product quality, and consequently software engineering does not have tools to freely manipulate the quality level for a product. This article proposes a simplified method to manipulate the observed quality level, thereby making it possible to conduct research. The proposed experiment has been conducted among professional software evaluators. The results show the significant negative influence (large effect size) of negative experience of users on final opinion about software quality regardless of its actual level.

Software Quality Assurance consists of monitoring the software engineering processes and ensuring the highest quality. But, the software quality attributes that we deal with are not explicit in the outset and cannot be easily measured. The same attribute has multiple significance and importance in multiple contexts. The user, the developer and the manager of a software product may have different stands regarding the significance of a quality attribute. A software quality engineer, while measuring the total software quality should provide appropriate weight to each of the decision makers. This chapter proposes a fuzzy multi-criteria approach to measure the total software quality and to identify the best alternative from a set of software products.

The aim of this study is the development of the method of generating and filling the template of ontology for the quality of the concrete software and method of forming the logical conclusion about the sufficiency of information of software requirements specification (SRS) for software quality assessment (by ISO 25010:2011). The first time proposed method of generating and filling the template of ontology for the quality of the concrete software leaves in the relevant ontology only measures, which are available in the SRS for the concrete software. It provides forming the ontology for the quality of the concrete software. The first time developed method of forming the logical conclusion about the sufficiency of the SRS information for software quality assessment provides the conclusion about the sufficiency or insufficiency of the SRS information for software quality assessment by ISO 25010:2011. If the SRS information is insufficient, this method: provides the conclusion for which characteristics and sub-characteristics the information is insufficient; creates the sorted list of missing measures as the recommended priority of their addition in the SRS; evaluates the veracity of software quality assessment based on the available in the SRS measures.

The research topic focuses on the characterization of software quality considering the main software elements such as people, process and product. Many attributes (size, language, testing techniques etc.) probably could have an effect on the quality of software. In this thesis we aim to understand the impact of attributes of three P's (people, product, process) on the quality of software by empirical means. Software quality can be interpreted in many ways, such as customer satisfaction, stability and defects etc. In this thesis we adopt ‘defect density' as a quality measure. Therefore the research focus on the empirical evidences of the impact of attributes of the three P's on the software defect density. For this reason empirical research methods (systematic literature reviews, case studies, and interviews) are utilized to collect empirical evidence. Each of this research method helps to extract the empirical evidences of the object under study and for data analysis statistical methods are used. Considering the product attributes, we have studied the size, language, development mode, age, complexity, module structure, module dependency, and module quality and their impact on project quality. Considering the process attributes, we have studied the process maturity and structure, and their impact on the project quality. Considering the people attributes, we have studied the experience and capability, and their impact on the project quality. Moreover, in the process category, we have studied the impact of one testing approach called ‘exploratory testing' and its impact on the quality of software. Exploratory testing is a widely used software-testing practice and means simultaneous learning, test design, and test execution. We have analyzed the exploratory testing weaknesses, and proposed a hybrid testing approach in an attempt to improve the quality. Concerning the product attributes, we found that there exist a significant difference of quality between open and close source projects, java and C projects, and large and small projects. Very small and defect free modules have impact on the software quality. Different complexity metrics have different impact on the software quality considering the size. Product complexity as defined in Table 53 has partial impact on the software quality. However software age and module dependencies are not factor to characterize the software quality. Concerning the people attributes, we found that platform experience, application experience and language and tool experience have significant impact on the software quality. Regarding the capability we found that programmer capability has partial impact on the software quality where as analyst capability has no impact on the software quality. Concerning process attributes we found that there is no difference of quality between the project developed under CMMI and those that are not developed under CMMI. Regarding the CMMI levels there is difference of software quality particularly between CMMI level 1 and CMMI level 3. Comparing different process types we found that hybrid projects are of better quality than waterfall projects. Process maturity defined by (SEI-CMM) has partial impact on the software quality. Concerning exploratory testing, we found that exploratory testing weaknesses induce the testing technical debt therefore a process is defined in conjunction with the scripted testing in an attempt to reduce the associated technical debt of exploratory testing. The findings are useful for both researchers and practitioners to evaluate their projects

For projects that rely on empirical process control and deliver frequently working versions of software, developers and project managers regularly need to examine the status of their software quality. This study illustrates that simple goal-oriented changes or extensions to the existing data of projects' respective defect tracking systems could provide valuable and prompt information to improve their software quality assessment and assurance.

Software quality issues play a dominant role in the development of large scale software systems. High quality software enhances reuse potential and facilitates software maintenance activities. However, at present, software quality assessment is a labor intensive, error prone, time consuming process. Automated quality assessment of software systems is a cost effective alternative to ensure compliance with system quality objectives. This paper discusses how reverse engineering technology can be leveraged to solve the needs of software quality assurance teams.< <ETX xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">&gt;</ETX>

: With regard to software testing in DoD, we can summarize our conclusions in two fundamental ideas. First, DoD knows how to produce quality software at low cost. This is because organizations such as DoD STEP, Army STEP, and Software Engineering Institute have already researched and documented policies for DoD. A few commercial software developers practice many of the DoD policies and directives now, and produce quality software (for example, IBM FSC Houston). Second, quality cannot be tested into software. Only a well-defined, well-disciplined process with a continuous improvement cycle can ensure software quality. However, testing cannot be underestimated. Systematic testing activities that detect error earliest in the life cycle are necessary to drive process improvement and optimize the development of quality software. Such testing methods as formal inspection find defects early. This enables cost- effective error resolution, identification and removal of defect causes, and thus, prevention of future defect insertion. If practiced with discipline, such methods can evolve a self-correcting software development process that is stable, modeled, measured, and therefore, predictable. This development process engineers quality software faster at reduced cost.... Software testing, Software quality, Formal inspection, Quality control.

Developing a good software system is a very complex task. In order to produce a good software product, several measures for software quality attributes need to be taken into account. System complexity measurement plays a vital role in controlling and managing software quality because it generally affects the software quality attributes like software reliability, software testability and software maintainability. Thus, software quality assurance (SQA) needs to be addressed keeping in view the new strategies, tool, methodologies and techniques applicable to software development life cycle.This paper is primarily aimed at revisiting and examining peculiar aspects of software development process that affect software quality management process. These aspects of software development process include software reliability measurement, ISO approach applicable to software quality and some aspects related to software testing improvement. Software testing and evaluation methods/tools/techniques do not guarantee effective testing and ensure high software quality. The way to improve the effectiveness of testing is to improve the attitude of software developers towards testing.In this paper, all these factors affecting software quality management have been discussed as well as all the possible improvements have been suggested. The results of this paper may be quite helpful to the researchers in quantifying the specific measuring tools for these software quality attributes.

Putting Requirements and Quality at the Core of Global Service Delivery: Current Efforts and Future Plans at Pace University

Software testing is an important process in software quality assurance(SQA). Software testing consumes the majority of the software developers' time and cost of all the phases of system development. An important problem in software testing is to determine whether a program has been tested enough with a testing criterion and when one could stop testing. On the other hand, software measurement is used to estimate the quality of a software. Complexity measures can be used to compare software quality and development cost. This paper proposes a new testing approach which choosing testing path based on path complexity. The process is to use a set of testing paths that satisfying all-uses testing criterion, and then choose the testing path with the most complexity to test. This process is continued until the program can be accepted. The proposed formula is used to determine if it is possible to stop testing before satisfying all-du-paths testing criterion. The main contribution of the paper is that software developers can choose a proper testing action with lower testing effort.

Quality of software is the key to successful software development and physics results transparency. An original method to assess the quality of scientific software systems objectively has been developed. A set of established software metrics is combined with statistical analysis methods, such as trend analysis and inequality and diversity measures, to quantify various characteristics of the code, such as maintainability. This methodology, previously applied to Geant4, has now been employed to assess the quality of ROOT, a software system for big data processing, statistical analysis, visualisation and storage frequently used in particle and nuclear physics experiments. Preliminary results of the analysis of ROOT software quality are presented.

To assure high software quality for large-scale industrial software systems, traditional approaches of software quality assurance, such as software testing and performance engineering, have been widely used within Alibaba, the world's largest retailer, and one of the largest Internet companies in the world. However, there still exists a high demand for software quality assessment to achieve high sustainability of business growth and engineering culture in Alibaba. To address this issue, we develop an industrial solution for software quality assessment by following the GQM paradigm in an industrial setting. Moreover, we integrate multiple assessment methods into our solution, ranging from metric selection to rating aggregation. Our solution has been implemented, deployed, and adopted at Alibaba: (1) used by Alibaba's Business Platform Unit to continually monitor the quality for 60+ core software systems; (2) used by Alibaba's R&D Efficiency Unit to support group-wide quality-aware code search and automatic code inspection. This paper presents our proposed industrial solution, including its techniques and industrial adoption, along with the lessons learned during the development and deployment of our solution.

The objectives of this chapter are threefold: 1. to motivate the necessity of establishing a software quality assessment program based on fundamental software engineering concepts, 2. to present the OPA Framework with Software Quality Indicators (SQIs) as a sound comprehensive approach to quality measurement, and 3. to relate process and product measures to the goals of prediction and assessment. KeywordsSoftware EngineeringSocial IndicatorSoftware QualityMeasurement GoalSoftware Engineering ProcessThese keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

Software quality assessment using a multi-strategy classifier

Assessing software quality and understanding how events in its evolution have lead to anomalies are two important steps toward reducing costs in software maintenance. Unfortunately, evaluation of large quantities of code over several versions is a task too time-consuming, if not overwhelming, to be applicable in general. To address this problem, we designed a visualization framework as a semi-automatic approach to quickly investigate programs composed of thousands of classes, over dozens of versions. Programs and their associated quality characteristics for each version are graphically represented and displayed independently. Real-time navigation and animation between these representations recreate visual coherences often associated with coherences intrinsic to subsequent software versions. Exploiting such coherences can reduce cognitive gaps between the different views of software, and allows human experts to use their visual capacity and intuition to efficiently investigate and understand various quality aspects of software evolution. To illustrate the interest of our framework, we report our results on two case studies.